Constant false alarm rate (CFAR) techniques are frequently utilized in radar receivers to prevent saturation of radar target detection and tracking processors. Target detection is a statistical process and as such requires an accurate characterization of target and clutter statistics for the determination of an optimal CFAR detection threshold. CFAR techniques rely on the adaptive update of receiver detection thresholds to maintain a constant probability of false alarm. The detection threshold must be adaptively updated to accommodate variations in the radar clutter background. Two parameter statistical models are generally required to accurately characterize radar clutter for a wide range of clutter types and conditions. The most commonly utilized clutter models include the lognormal and the Weibull statistical distributions. An accurate description of radar clutter utilizing either of these statistical distributions amounts to the determination of the two model parameters.
The utility of these two parameter models has been limited by a lack of methods for estimating the parameters. Currently, practical CFAR techniques consist of radar resolution cell averaging schemes for the estimation of the clutter mean. These cell averaging schemes utilize an estimated clutter mean and empirically established values of the model "shape" parameter associated with the clutter type to set a detection threshold. In addition, the utilization of clutter mean estimates and the estimation of clutter means from a finite number of clutter samples requires the computation of complex threshold coefficients in the determination of a detection threshold. Inaccuracies in the determination of the clutter mean result in cell averaging CFAR threshold that are larger than the optimal values. The cell averaging CFAR thresholds result in a reduction in the probability of target detection. Ideally, it would be desirable to calculate optimal CFAR thresholds directly from known clutter model parameters. Aspects of the current state-of-the-art in cell averaging CFAR in traditional radar processors are briefly described in the following U.S. Patents, the disclosures of which are incorporated herein by reference:
U.S. Pat. No. 4,586,043 issued to Mary Wolf;
U.S. Pat. No. 4,532,639 issued to Price et al;
U.S. Pat. No. 4,513,286 issued to Irabu;
U.S. Pat. No. 4,293,856 issued to Chressanthis;
U.S. Pat. No. 4,103,301 issued to Evans;
U.S. Pat. No. 3,995,270 issued to Perry et al;
U.S. Pat. No. 3,968,490 issued to Gostin; and
U.S. Pat. No. 3,701,1498 issued to Patton et al.
The above-cited patents all describe radar CFAR processors. Monopulse techniques provide standard methods of accurate angular positioning in radar tracking systems. There remains a need for a monopulse scheme for the collection and processing of clutter samples is presented that allows for the simultaneous estimation of both the clutter mean and variance. The estimated clutter mean and variance should allow the calculation of both clutter model parameters. Knowledge of the clutter model parameters should allow for a simple calculation of the optimal CFAR detection threshold. The present invention is intended to satisfy these needs.